Neurophysiological Features of STN LFP Underlying Sleep Fragmentation in Parkinson's Disease
Parkinson’s Disease (PD) is a neurodegenerative disease primarily characterized by dopaminergic neuron damage. Aside from causing motor disorders, over 80% of Parkinson’s disease patients also suffer from sleep disorders. Fragmented sleep is a common type of sleep disturbance among PD patients. It is associated not only with sleep maintenance insomnia and excessive daytime sleepiness but also with exacerbating cognitive dysfunction and accelerating disease progression. However, the neurophysiological mechanisms causing fragmented sleep in PD patients are not fully understood, posing an obstacle to the development of targeted sleep intervention measures.
The authors of this study are from Tsinghua University, Beijing Tiantan Hospital of Capital Medical University, Qilu Hospital of Shandong University, Beijing Tsinghua Changgung Hospital, and the University of Oxford. In this original research, published in the Journal of Neurology, Neurosurgery & Psychiatry in 2024, they explored thalamic subthalamic nucleus (STN) local field potential (LFP) biomarkers related to fragmented sleep through simultaneous recording of whole-brain polysomnography and STN LFP in 13 post-deep brain stimulation (DBS) PD patients.
The research methodology mainly included the following steps:
a) Subjects: 13 PD patients who underwent bilateral STN DBS implantation 1 month prior. Whole-brain polysomnography and real-time wireless recording of STN LFP were conducted overnight in the state of DBS stimulation off and medication off.
b) Sleep assessment: Two sleep experts marked EEG data every 30 seconds into wakefulness, rapid eye movement (REM) sleep, N1, N2, or N3 sleep stages according to the American Academy of Sleep Medicine guidelines.
c) Data processing: EEG and LFP signals were filtered and denoised. The power of different frequency bands (δ, θ, α, β, low γ) was calculated, and sleep spindles and β burst events were detected.
d) Statistical analysis: Differences in LFP power across different sleep stages were analyzed. The Sleep Fragmentation Index (SFI) and Arousal Index (ARI) were calculated, and the correlation between LFP characteristics and SFI, ARI was explored. The relationship between sleep spindles, β bursts, and sleep transitions was analyzed.
The main findings of the study include:
1) Before transitions to N2 and REM sleep, the low-to-high frequency power ratio (LHPR) of thalamic STN LFP (θ waves to β and low γ waves) can serve as a biomarker for fragmented sleep. Lower LHPR was negatively correlated with SFI and ARI.
2) During NREM sleep, STN LFP β and low γ power were positively correlated with SFI and ARI. During REM sleep, only low γ power was positively correlated with SFI.
3) During NREM N2 sleep, longer β bursts (>0.25 seconds) were more likely to appear when transitioning to lighter sleep stages such as wakefulness/N1/REM, while sleep spindles were more likely to appear when transitioning to deeper N3 sleep stages. A temporal negative correlation existed between long β bursts and sleep spindles.
4) There was a clear distinction between the peak frequencies of STN spindles (11.5 Hz) and long β bursts (23.8 Hz), indicating that they are different physiological and pathophysiological processes.
This study elucidates the neurophysiological mechanism underlying fragmented sleep in Parkinson’s disease by examining STN LFP characteristics, providing a basis for the further development of targeted interventions, such as closed-loop DBS, to improve sleep quality and the quality of life for PD patients. The study also suggests that when designing closed-loop DBS algorithms, oscillatory activities across multiple frequency bands and differentiation from physiological sleep spindles need to be considered.
From a neuro-electrophysiological perspective, this research deeply explores the mechanisms causing fragmented sleep in Parkinson’s disease patients, filling a research gap in the field and offering significant clinical translational value.